The goal of hydrocarbon exploration is to find porous and permeable geologic deposits containing high pore-space saturations of hydrocarbons, under sufficient pressure to allow some mode of commercial production. In pursuit of this goal, companies, countries and individuals collect and process many types of geophysical and geological data. The data is often analyzed to find anomalous zones that can reasonably be attributed to the presence of hydrocarbons.
The usage of 2D and 3D seismic data anomalies has been a standard practice in the petroleum industry since the 1960s. Other geologic and geophysical data anomalies have been tried, sometimes successfully, for over a century. These includes various gravimetric, electromagnetic, chemical, biological and speculative methods.
The usage of anomalies for oil and gas detection has been plagued by several problems. First, most remote sensing anomalies (e.g., a 3D seismic amplitude anomaly) cannot be directly tied to a rock property that could be measured in the laboratory or using well logs. Much effort is expended attempting to tie observed anomalies to known rock responses by modeling the expected attribute response or otherwise correlating with a known producing reservoir. This work is often based on the experience of the practitioner.
A second problem is that the anomalies themselves are often evaluated or tied to response models in a qualitative manner. With qualitative assessment as the basis, quantitative, objective and reproducible error analysis has not been possible.
A third problem is that a basic physical property at work is hydrocarbon reservoirs is that both oil and gas are less dense than water. This generally causes oil and gas to accumulate up-structure in the pore-space of potential reservoir rocks. The higher water saturations are found, generally, down-structure. This separation of saturations is driven by gravity. When such a separation of fluid types occurs, flat interfaces, in depth, are expected to form.
This separation causes numerous possible classes of data attribute response. First, the hydrocarbon reservoir will have one response for each hydrocarbon type. The water-saturated part of the reservoir may have a second data response and the interfacial area a third type of attribute data response. In this sequence of responses, neither the water saturated reservoir response nor the single component hydrocarbon saturated reservoir response are expected to vary with structural position. The transition from one type of fluid saturation to another, having a different density, is expected to occur at a single depth or seismic travel time within the attribute data set. This change from saturation state to another at a given depth and location should be detectable using a quantitative tool.
The present invention is designed for the detection, quantification and evaluation of the depth and location of interface between lighter and heavier saturating fluids as exhibited in a data attribute dataset. It is designed to quantify the change in a data attribute in the up structure direction from an interpreted water reservoir to the hydrocarbon reservoir part of the dataset. The invention has been designed to overcome these known problems in the art.